Principal Investigator: Professor David Melzer
Department: Epidemiology and Public Health
Institution: University of ExeterTags: 14631, age related disease, ageing, high functioning
Lead Collaborators: Professor Carol Brayne
Collaborating Institutions and Addresses: University of Cambridge, Public Health and Primary Care, Forvie Site, Robinson Way, Cambridge CB2 0SR, UK
1a: We aim to identify risk factors and genetic variants associated with ageing well – i.e. having the best health status in the seventh decade of life
We aim to identify factors associated with being free of major ageing diseases (cardiovascular disease, stroke, diabetes, depression or cancer) and consistently in the healthiest range of measures such as muscle strength, cognition, lung function, bone mineral density and blood pressure and key blood tests.
Genome wide association studies (GWAS) will identify associated variants for the summary phenotype and for the main components included.
This project has been funded by the Medical Research Council.
1b: Our underlying aim is to find new ways of helping those who develop earlier onset age-related disease and loss of function, by applying insights gained from those who age well. The conventional and genetic factors associated with ageing well should help reveal the underlying mechanisms and perhaps provide markers for identifying early problems or monitoring progression in each of the components of ageing well.
1c: This project involves analysis of the existing data, with collaborations to allow independent replication of findings.
We will use statistical methods to optimize the classification of ageing well and its component traits. We will pay particular attention to those in the seventh decade of life, but also examine associations in younger groups and test for interactions with advancing age. We will use standard statistical modelling approaches to identify and characterise conventional measures associated with ageing well. We will also use genome wide association study approaches to identify genetic variants statistically associated with ageing well and its components.
1d: The full cohort, with special focus on the 217000 respondents aged 60 to 69 at baseline